Users of the Atlas sometimes ask: Where does the data come from? This page is
in response to that question. The UC Atlas of Global Inequality draws on data
from a variety of sources. The main source of data for Atlas maps and the Atlas
database is the World Bank's World Development
Indicators. Other data sets are used for some maps, figures, graphs and
tables. As new content is added, additional data sets will be used and added to
the database.

Data Collection Process

Most data in the World Bank WDI dataset comes from the governments of
individual countries. The World Bank collects data on living standards and
debt, but not much else. Some also comes from various international and
national agencies with which World Bank partners (see world bank partners
http://www.worldbank.org/data/wdi2004/partners.pdf for more info).

The following provides a rough outline of the data collection process for the
World Bank data set. Several other global agencies, such as the IMF, the
UN Development Program, and the World Health Organization, collect data from
national governments in a simlar way.

Because data is collected by many governments, differences in
methods and conventions may cause discrepancies when comparing data
between countries and over time. These, and other data limitations, are
described below.

Limits on the data

There are many sources of error and omission in the data. Here we describe three.

Averaged and aggregated data

Most of the numbers generated by international agencies, including the
World Bank, are national averages. Nation-states have become the
principal units through which we view the world and understand global
change. For many purposes national numbers have utility. But such
numbers overlook the diversity of conditions facing rich and poor,
women and men, minorities and majorities. Ideally, national measures
should be supplemented by indicators of the spread of the results
across social and economic divides.

Omissions and priorities

Some numbers are collected and others are not. Frequently, there are
historical reasons for these omissions associated with the goals of the
collecting agency. Important omissions for the student of inequality
include: distributions of wealth, income, representation and power
across social divides of class, gender and ethnicity.

Since 1990, a limited global debate about the measurement of social
progress has been occurring between the UN Development Program (UNDP)
and the World Bank. With the publication of the UNDP's Human
Development Report, the range of numbers about national populations has
been expanded. The Human Development Report took up ideas suggested by
Amartya Sen that social progress could be more effectively measured
through social outcomes, such as life expectancy and infant mortality,
rather than through measures of economic output, such as Gross National
Product. The Human Development Report developed the Human Development
Index (HDI) as a measure of national achievement. The HDI provides a
single indicator reflecting life expectancy, literacy and Gross
Domestic Product.

Errors and Biases

In addition to errors arising from the priorities of government
collection agencies and differences in methods of data collection,
there are some important biases in these data. Effectively all economic
data excludes work that is not monetized. This means that global
statistics exclude all domestic work, done primarily by women, and may
provide poor estimates of production for direct consumption. These
exclusions may bias statistics about income (GDP) and work (employment,
labor force).

Checks

To deal with problems of statistical distortion, agencies that collect and
distribute final national data sets in global reports, specifically the World
Bank and the UNDP, have established a framework to promote consistency and
accuracy between indicators and countries. At the core of this framework is
the United Nations' Fundamental
Principles of Official Statistics , which was established following the
collapse of the Soviet Union as the former Soviet bloc transitioned to market
economies. This document covers the wide range of scientific and ethical
issues inherent in the collection and dissemination of national statistics that
every country and agency submitting the data must abide by. The International
Monetary Fund and the World Bank have taken an additional step in developing
the General
Data Dissemination System (GDDS) which is intended to improve data
collection, analysis and reporting techniques, as well as the Data Quality
Assessment Framework (DQAF) which combines the Fundamental Principles of
Official Statistics, the GDDS, and other "best practices and
internationally accepted concepts and definitions in statistics." This set
of dissemination standards is intended to promote fairness, accuracy, and
comparability in data sets between countries.

As global numbers
are more widely distributed it is likely that independent estimates and
comparisons, by agencies and individuals outside government and
international organizations, will be generated.